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The fast Fourier transform and its applications E. Brigham
Publisher: Prentice Hall

This article is making reference to Maxim's AN3722 "Developing FFT Applications with Low-Power Microcontrollers" that turned very difficult to find, as Maxim apparently wiped it from its servers! It breaks down a signal into sinusoids of different frequencies transforms from time domain to frequency domain. Ø Transient, intermittent behavior. The supported NVIDIA GPU routines include both a range of dense linear algebra algorithms and 1D & 2D Fast Fourier Transforms (FFTs). This is a method to calculate the discrete Fourier transform and its inverse. The bold face line (bold added) reports that we have successfully created a FFT object that will execute its 2100-point FFT's on the GPU. Ø Suitable for time-varying phenomena. Frequently applications need to solve similarly sized problems repeatably and the threshold can be adjusted to place the computation where needed. Ø Long-lived, stationary signals. Ø Suitable for time invariant signal. Gilbert Strang, author of the classic textbook Linear Algebra and Its Applications, once referred to the fast Fourier transform, or FFT, as “the most important numerical algorithm in our lifetime.” No wonder. Deal with expansion of functions in terms of a set of basic functions.